Effects of capital flow restrictions: Evidence of welfare improvement

Abstract

The study examines the distributional implications of capital account restrictions on three important welfare measurements of concern for policymakers: income inequality, poverty, and external debt. Two approaches are followed, the Autoregressive Distributed Lag (ARDL), and the local projections regression with impulse response functions (IRFs), and applied to a panel data for 102 countries from 1995 to 2019. First, we identify the capital control periods, and second, we follow behavior of these three measurements after these periods. The results show a decline in income inequality and poverty and a decline in debt to foreigners. However, four pathways can affect the intensity of capital controls impacts. First, the financial development and the strength of the financial institutions have a significant role in shaping how these three welfare measurements respond to capital control reforms, specifically over 5 years. Second, capital controls can reduce financial crisis probability, and with tighter capital controls particularly following the 2008 financial crisis, the impacts become clearer. Third, the bargaining power of the labor market is strengthened in the aftermath of controls and consequently reduces inequality and poverty. Finally, through the cost of international debt, capital controls establish a new channel lowering foreign debt.

KEYWORDS:

• Capital controls
• inequality
• poverty
• external debt

JEL Classifications:

• F30
• F36
• F37
• F43

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 This approach is used thereafter by Furceri and Loungani, (2019); Bernal-Verdugo, Furceri, and Guillaume (2013).

2 The study apply the logarithm of these variables.

3 We refer to the results of Akaike information criterion to choose two lags on the variables.

4 5 years is the IRFs time horizon.

5 The data of this variable was tacked from the UN national accounts, table 203.

Additional information

Funding

This study is supported via funding from Prince Sattam bin Abdulaziz University project number [PSAU/2023/R/1444].